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<p>Urban green spaces offer several economic, social, and health benefits to residents. This study was conducted to identify the appropriate locations of green spaces in the Eka Tafo Sub-City using geospatial technologies, namely Geographic Information System (GIS) and Remote Sensing (RS). Eight parameters were evaluated: slope, normalized difference vegetation index (NDVI), proximity to rivers, elevation, land use, soil type, proximity to highways, and population density. The Analytical Hierarchy Process (AHP) was used to assign weights to each factor. The green space suitability map was generated by integrating all the thematic layers in ArcGIS. The green space map identifies five suitability zones: highly suitable, suitable, moderately suitable, poorly suitable, and unsuitable. The findings showed that approximately 30.7% of the study area was classified as suitable to highly suitable for green space, whereas 40.7% was considered unsuitable to poorly suitable. These results enable policymakers to determine the open green spaces that enhance the environmental quality of urban areas and the living standards of residents.</p>

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Green space suitability assessment for sustainable urban development using geospatial technology in Eka Tafo, Ethiopia

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月10日

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  • Dechasa Diriba,
  • Ebassa Dugasa Leta,
  • Degu Demise,
  • Melion Kasahun,
  • Shankar Karuppannan,
  • Negedie Abrha Gebreslassie,
  • Tesfaye Lemma,
  • Mesay Mengistu Feyisa

摘要

Urban green spaces offer several economic, social, and health benefits to residents. This study was conducted to identify the appropriate locations of green spaces in the Eka Tafo Sub-City using geospatial technologies, namely Geographic Information System (GIS) and Remote Sensing (RS). Eight parameters were evaluated: slope, normalized difference vegetation index (NDVI), proximity to rivers, elevation, land use, soil type, proximity to highways, and population density. The Analytical Hierarchy Process (AHP) was used to assign weights to each factor. The green space suitability map was generated by integrating all the thematic layers in ArcGIS. The green space map identifies five suitability zones: highly suitable, suitable, moderately suitable, poorly suitable, and unsuitable. The findings showed that approximately 30.7% of the study area was classified as suitable to highly suitable for green space, whereas 40.7% was considered unsuitable to poorly suitable. These results enable policymakers to determine the open green spaces that enhance the environmental quality of urban areas and the living standards of residents.